Classification, Estimation and Adaptation of Error Control Coding
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The omnipresent and omnipotent noise can cause havoc to the data transmitted by the user. In the modern scheme of wireless systems, fading happens which is literally the last straw on the camel's back. In the context of ever rising demand for online and wireless applications, it is a real challenge to control error caused by both noise and fading. Sometimes, we may find ourselves in a situation where the coding parameters are unknown to us while it is also necessary for us to retrieve the information. We have shown a way to classify and estimate coding parameters. Also, a second situation exis...
The omnipresent and omnipotent noise can cause havoc to the data transmitted by the user. In the modern scheme of wireless systems, fading happens which is literally the last straw on the camel's back. In the context of ever rising demand for online and wireless applications, it is a real challenge to control error caused by both noise and fading. Sometimes, we may find ourselves in a situation where the coding parameters are unknown to us while it is also necessary for us to retrieve the information. We have shown a way to classify and estimate coding parameters. Also, a second situation exists wherein the channel keeps varying with time and on application of fixed code rate error control mechanism, we find it is less efficient. The conservative approach would be just to make use of minimum code rate so as to mitigate maximum fading. Adaptive Modulation and Coding (AMC) is the known approach to such an issue - wherein the coding parameters are adapted as per the fading conditions. We have ventured into AMC as well. Interestingly we can study the DNA sequencing also through estimating the coding sequence. Also we have employed Turbo codes which are nearing Shannon limit -1,6 dB.
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